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Maxima and Minima

In this lesson you’ll learn how to find where a function reaches its highest and lowest values, both locally and on a closed interval. This is the foundation for optimization problems.

A critical point is where f’(x) = 0 or f’(x) doesn’t exist. These are the only places where a local max or min can happen. If the derivative exists and isn’t zero, the function is either going up or going down, so there’s no peak or valley.

At a local maximum (left), the function rises (f’ positive, green arrow) then falls (f’ negative, red arrow). The tangent line is horizontal at the peak. At a local minimum (right), the function falls then rises. The tangent line is horizontal at the valley.

Check the sign of f’ on either side of a critical point:

  • f’ goes from positive to negative: local maximum (the function was rising, now it’s falling)
  • f’ goes from negative to positive: local minimum (the function was falling, now it’s rising)
  • f’ doesn’t change sign: no extremum (just a flat spot)

At a critical point c where f’(c) = 0:

  • f”(c) is positive: local minimum (concave up, like a bowl)
  • f”(c) is negative: local maximum (concave down, like a hill)
  • f”(c) = 0: inconclusive, use the first derivative test instead

On a closed interval [a, b], the absolute max and min must occur at either a critical point inside the interval or at one of the endpoints. Evaluate f at all candidates and compare.

Example 1: First Derivative Test

Find the local extrema of f(x) = x³ - 3x² - 9x + 5.

f(x)=3x26x9=3(x22x3)=3(x3)(x+1)f'(x) = 3x^2 - 6x - 9 = 3(x^2 - 2x - 3) = 3(x - 3)(x + 1)

Critical points: x = -1 and x = 3.

Check the sign of f’ in each interval:

  • x less than -1: f’(-2) = 3(4 + 4 - 3) = 15, positive (rising)
  • Between -1 and 3: f’(0) = 3(0 - 0 - 3) = -9, negative (falling)
  • x greater than 3: f’(4) = 3(16 - 8 - 3) = 15, positive (rising)

f’ goes from positive to negative at x = -1: local max. f’ goes from negative to positive at x = 3: local min.

Example 2: Second Derivative Test

For f(x) = x⁴ - 4x², find and classify the critical points.

f(x)=4x38x=4x(x22)f'(x) = 4x^3 - 8x = 4x(x^2 - 2)

Critical points: x = 0, x = sqrt(2), x = -sqrt(2).

f(x)=12x28f''(x) = 12x^2 - 8

f”(0) = -8, which is negative: local max at x = 0. f”(sqrt(2)) = 12(2) - 8 = 16, which is positive: local min at x = sqrt(2). f”(-sqrt(2)) = 16, positive: local min at x = -sqrt(2).

Example 3: Absolute extrema on [0, 5]

Find the absolute max and min of f(x) = x³ - 6x² + 9x + 2 on [0, 5].

f(x)=3x212x+9=3(x1)(x3)f'(x) = 3x^2 - 12x + 9 = 3(x - 1)(x - 3)

Critical points in [0, 5]: x = 1 and x = 3.

Evaluate f at all candidates:

  • f(0) = 2
  • f(1) = 1 - 6 + 9 + 2 = 6
  • f(3) = 27 - 54 + 27 + 2 = 2
  • f(5) = 125 - 150 + 45 + 2 = 22

The absolute maximum is 22 at x = 5 (the right endpoint). The absolute minimum is 2, occurring at both x = 0 and x = 3. The local max at (1, 6) is not the absolute max because the endpoint at x = 5 is higher. This is why you always check endpoints on closed intervals.

Finding maxima and minima is the core of optimization:

  • Business: maximize profit or minimize cost given constraints
  • Engineering: find the dimensions that maximize strength while minimizing material
  • Physics: find the angle that maximizes projectile range, or the path that minimizes travel time
  • Medicine: find the dosage that maximizes effectiveness while minimizing side effects
A critical point occurs where:
If f' changes from positive to negative at a critical point, there is a:
The Second Derivative Test is inconclusive when:
On a closed interval [a, b], absolute extrema can occur at:
If f''(c) is positive at a critical point c, then c is a: